An efficient down/upsampling method to compress a depth map efficiently within the high-efficiency video coding (HEVC) framework is presented. A different edge-preserving depth upsampling method is proposed by using both the texture and depth information. We take into account the edge similarity between depth maps and their corresponding texture images as well as the structural similarity among depth maps to build a weight model. Based on the weight model, the optimal minimum mean square error upsampling coefficients are estimated from the local covariance coefficients of the downsampled depth map. The upsampling filter is combined with HEVC to increase coding efficiency. The objective results demonstrate that we achieve a maximum bit rate saving of 32.2% compared to full resolution method and 27.6% compared to a competing depth down/upsampling method on depth bit rate. The subjective evaluation showed that our proposed method achieves better quality in synthesized views than existing methods do.
The sensitivity of channel bit error rate (BER) to the turbo coding parameters (i.e., code rate, iterative number and interleave length, etc) and the wireless channel statistic enlightens us to model a BER for turbo coding over Rayleigh channel. The model presented in this paper synthetically considers and quantificationally analyzes the impacts of all the coding parameters and the wireless channel statistic on the BER, and then emphasizes a simple equation that relates the BER at the encoder to the relevant coding parameters. Based on this model, the BER performance can be estimated even before channel coding given certain coding parameters set and channel statistic. The simulation results show that the model can handle the actual values with high accuracy. The maximal average predictive error is around 0.07%. Moreover, the proposed model is very regular and simple, and can be extended to other cases. These characteristics will make it more useful in practice.